关键词: 流程挖掘, 紧邻关系, 关系数据库, 实验对比, ProM平台

Abstract: As the most popular media for large-scale data,relational databases record amount of event logs during the operation of information system.However,traditional process mining techniques mainly deal with event logs in XES format,and every mining task needs to manually export the latest log file from the database.The whole process is very tedious,and it cannot make full use of the powerful data processing capacity of relational database.For these problems,the process mining strategy and algorithm for relational log were studied.To improve the process mining efficiency for relational logs,an approximate linear mining algorithm with high universal was proposed based on the fast sorting capability of relational database for large-scale event logs stored in relational databases,which had less invasive to the business database.The algorithm had been implemented on ProM platform,and the experiment based on large-scale event log showed the high efficiency of the proposed method.

Key words: process mining, directly-follow relation, relational database, experimental comparison, ProM platform